class_docstr: Tests for bbox_overlap
  bbox_overlap has a TensorFlow and a Numpy implementation.
  
  We test both at the same time by getting both values and making sure they
  are both equal before doing any assertions.
code: def testInvalidBoxes(self):
      # Zero area, bbox1 has x_min == x_max
      iou = self._get_iou([[10, 0, 10, 10]], [[0, 0, 10, 10]])
      # self.assertAllEqual(iou, [[0.]]) TODO: Fails
  
      # Negative area, bbox1 has x_min > x_max (only by one)
      iou = self._get_iou([[10, 0, 9, 10]], [[0, 0, 10, 10]])
      self.assertAllEqual(iou, [[0.0]])
  
      # Negative area, bbox1 has x_min > x_max
      iou = self._get_iou([[10, 0, 7, 10]], [[0, 0, 10, 10]])
      self.assertAllEqual(iou, [[0.0]])
  
      # Negative area in both cases, both boxes equal but negative
      iou = self._get_iou([[10, 0, 7, 10]], [[10, 0, 7, 10]])
      self.assertAllEqual(iou, [[0.0]])
  
file_path: luminoth/luminoth/utils/bbox_overlap_test.py
imports: import numpy
  import tensorflow
  from luminoth.utils.bbox_overlap import bbox_overlap_tf, bbox_overlap
label_desc: Use image node_id 5 for calling the BBoxOverlapTest obj's underlying member method code with example usage: obj.testInvalidBoxes() without return types